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12-Jun-2018 New paper shows that one in five taxonomy annotations in SILVA and Greengenes are wrong.

18-Apr-2018 New paper shows that taxonomy prediction accuracy is <50% for V4 sequences.

05-Oct-2017 PeerJ paper shows low accuracy of closed- and open-ref. QIIME OTUs.

22-Sep-2017 New paper shows 97% threshold is wrong, OTUs should be 99% full-length 16S, 100% for V4.

24-Nov-2016
UPARSE tutorial video posted on YouTube. Make OTUs from MiSeq reads.

 

USEARCH v11

Diversity analysis

ImageSee also
  OTU / denoising pipeline
  Alpha diversity
  Beta diversity
  Microbial taxonomy
  Rarefaction
  Which taxonomy database should I use?
  Interpreting diversity metrics
  Recommended alpha and beta metrics
  Comparing alpha diversity between groups
  Statistical significance of diversity differences
 

Diversity analysis investigates questions such as "how many species are in a sample?" and "how similar are these two samples?". The diversity in a single sample is called alpha diversity, and the diversity (differences or similarities) between two samples is called beta diversity.

The input data used for diversity analysis is an OTU table. A tree for the OTUs is also needed for UniFrac beta diversity analysis, this can be created using the cluster_agg command.

Usearch supports diversity analysis through the alpha_div, alpha_div_rare and beta_div commands. These commands support several popular diversity metrics.

You can visualize diversity using octave plots.

Note that most standard diversity metrics are difficult to interpret or invalid for NGS OTUs.

You can test  for statistically significant differences in alpha diversity between groups by using the alpha_div_sig command.
 
Taxonomy for the OTU sequences can be predicted using the sintax command
. See also Which taxonomy database should I use?
 
A tree for the OTU sequences can be generated using the cluster_aggd command
.